$70  / per hour

Years of experience



I am currently a Senior Data Engineer Consultant at Credit Suisse in Zürich, where I lead the development of key risk management tools. My responsibilities include planning the long-term vision, coordinating data acquisition, and building technological infrastructure for various projects. One of my notable achievements is creating a proprietary graph-analysis application to track critical dependencies across several branches, which has improved risk management efficiency. Additionally, I designed and implemented PySpark algorithms to process 10GB of structured batch data daily, as well as a real-time anomaly detection tool in Python and Scala, which enhances data quality monitoring. My technical skills include Java, JavaScript, Python, Spark, Hive, Neo4J, Oracle DB, Docker, Kubernetes, Jenkins, and AWS. Previously, I worked as a Senior Machine Learning Engineer at Clear Artificial Intelligence Ltd in London. During my tenure, I performed PPE demand forecasting for NHS Trusts using statistical methods in Python, which helped optimize supply and reduce costs during the first Covid-19 wave. I also developed a recommender system for Nestlé Canada's online store, boosting B2B sales by 25%. My role involved utilizing Python for various machine learning applications, including collaborative filtering and content-based approaches. My technical expertise includes Python, JavaScript, Spark, Hive, Neo4J, PostgreSQL, Docker, and Google Cloud Platform. I hold an MBA from the University of the People and a Master of Science in Computer Science from the University of Bari Aldo Moro, complementing my extensive experience in data engineering and machine learning.

Tech Stack

Neo4j, AWS, Docker, Hive, Java, JavaScript, Jenkins, Kubernetes, Oracle, Python, Spark


  • Formulated a long-term strategy, managed data acquisition, and established the technical framework for the UK and US branches at Credit Suisse
  • Mapped and monitored crucial dependencies between data from various Credit Suisse departments (EMEA, UK, and Swiss branches).
  • Handled 10GB of structured batch data daily to detect and escalate potential event-driven risks for the Risk Management & Compliance department.
  • Used Python and Scala to design a tool that identified and escalated potential data quality issues for the Production support team.
  • Applied statistical methods in Python to optimize supply and reduce costs during the initial Covid-19 wave in the UK.
  • Developed a system using collaborative filtering and content-based methods, which increased B2B sales by 25%.
  • Designed a crawler to download, tag, and organize information released by the UK Gov, and applied machine learning techniques to private company valuations, cutting process time by 18%.

Employment history

Senior Data Engineer Consultant, Credit Suisse July 2020 – Present

• Led the development of a new risk escalation & reporting tool for Credit Suisse (UK and US branches). Planned long-term vision, coordinated data acquisition, and built the technological infrastructure
• Led the development of a proprietary graph-analysis application to identify and track the critical dependencies between the data generated by several Credit Suisse departments (EMEA, UK and Swiss branches)
• Designed and implemented a PySpark algorithms working on 10GB of structured batch data ingested daily to identify and escalate potential event driven risks for the Risk management & Compliance department
• Designed and implemented a real-time anomaly detection tool (in Python and Scala) for the Production support team to identify and escalate potential data quality issues

Senior Machine Learning Engineer, Clear Artificial Intelligence Ltd July 2019 – June 2020

• Performed the PPE demand forecasting using statistical methods in Python (MA, ARMA, VAR). The results were used by the NHS Trusts to optimise their supply and decrease costs during the 1st Covid-19 wave in the UK
• Utilized Python to implement a recommender system (based on both collaborative filtering and contentbased approaches) for the Nestlé Canada online store, which boosted the total B2B sales by 25%

Machine Learning Engineer, HUBX February 2018 – June 2019

• Developed an HTML crawler to download, tag and arrange private companies’ information released by the UK Gov. Trained models for text segmentation and keyword extraction
• Utilized Python to implement several machine learning techniques (SVM, Random Forest, XGBoost) for private companies’ valuation on 30GB of unstructured data, which reduced the total process time by 18%

Data Engineer Consultant, Exprivia Spa February 2016 – January 2018

• Developed several Spark jobs on high performance computing Linux cluster to automate the systemic risk modelling for the Risk management & Compliance department of UniCredit Spa
• Analysed client export datasets by identifying key correlating metrics and conducting time series analysis using R

Education history

University of the People June 2019 – September 2020 Master of Business Administration (MBA)
• Final grade: 3.89/4.0
• Relevant Coursework: Financial management, Managerial accounting, Operations management, Competitive strategy, Managing in the global Economy, Business law, Leadership theory
University of Bari Aldo Moro October 2016 – December 2018 Master of science in Computer Science
• Final grade: 109/110
• Relevant Coursework: Stochastic calculus, Optimisation methods, Time series analysis, Big data analytics, Computational intelligenc, Deep learning, Reinforcement learning, Natural language processing, Topics in Artificial Intelligence
University of Bari Aldo Moro October 2012 – July 2016 Bachelor of science in Computer Science
• Final grade: 106/110
• Relevant Coursework: Statistical theory, Linear algebra, Numerical analysis, Software engineering, Object oriented programming in C++, Databases, Machine learning, Project management
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